James Chu
Phillip Pace is a distinguished professor (emeritus) in the Department of Electrical and Computer Engineering at the Naval Postgraduate School (NPS) and has also taught as an adjunct professor at Southern Methodist University. He was a senior scientist at L3Harris Technologies, Advanced Systems & Technologies, Plano, TX, USA, from 2020 to 2022. He received B.S. and M.S. degrees from Ohio University in 1983 and 1986, respectively, and a Ph.D. degree from the University of Cincinnati in 1990—all in electrical and computer engineering.
Developing Digital RF Memories and Transceiver Technologies for Electromagnetic Warfare
Dr. Pace was the Chairman of the N2/N6 Threat Missile Simulator Validation Working Group for 21 years and was one of four members on the U.S. Navy’s Nulka missile defense decoy system Blue Ribbon Panel in 1999. He is the founding director of the NPS Center for Joint Services Electronic Warfare. He has more than 80 refereed conference papers, 11 patents, and 36 refereed transactions, journal, and magazine publications. Dr. Pace was a technical editor of IEEE Transactions on Aerospace and Electronic Systems. He was a recipient of the U.S. Department of Defense Superior Civilian Service Medal and is a life member of the Association of Old Crows and a Fellow of IEEE.
This book grew out of the author’s teaching and research in the field of microwave photonic transceiver design for electromagnetic warfare at the U.S. Naval Postgraduate School. It has become evident that RF transceivers for digital RF memory (DRFM) are seeing an unprecedented level of growth in performance and capability.
The book is divided into two parts. Part I (Chapters 1–7) is on the concept of embedded transceiver design and architecture development for electromagnetic spectrum (EMS) dominance and electromagnetic maneuver warfare. It examines the design by bringing together a host of techniques and solutions to provide a comprehensive treatment of the technologies used in modern DRFM transceivers. Recent antenna and microwave photonic receiver technologies are also discussed for wideband spectrum sensing.
Part II (Chapters 8–11) introduces the concepts and techniques of modern spectral sensing using artificial intelligence (AI) and machine learning (ML) for emitter modulation classification and electronic attack (EA) for countertargeting to interrupt the kill web. Special emphasis is placed on EA techniques to create false targets against high-range resolution profiling radar systems, such as synthetic aperture radar (SAR) and inverse SAR. A final chapter is included on recent counter-DRFM techniques, discussing the methods used to defeat DRFM.
Chapter 1, “Electromagnetic Spectrum Dominance,” begins with a discussion of the electromagnetic spectrum as a domain and the role of DRFM in electromagnetic warfare. Airborne, surface, and subsurface unmanned systems that can participate in spectrum warfare are discussed, and the roles of unmanned systems and electromagnetic maneuver warfare are emphasized. DRFM architecture and both active and passive electronically scanned antennas are introduced. Measures of effectiveness in the observe, orient, decide, and act loop are examined. The author also explains the terms STITCHES, mosaic warfare, AI, and many more.
Chapter 2, “Digital RF Memory Receiver Architectures,” introduces the different architectures used for DRFM transceivers, including amplitude sampling, phase sampling, and channelized kernels. Also included is an overview of GPS receivers and the AI and ML techniques that are being used to improve the performance of the global navigation satellite system and its robustness and resistance to EA. These include amplitude analyzing architectures, phase sampling kernels, and channelized phase sampling kernels.
Chapter 3, “Designing DRFM AESA Antennas,” presents the recent progress in active electronically scanned antennas (AESAs) that are compatible with DRFMs. Analog, digital, and hybrid beamforming concepts are introduced. Transmit/receive module schematics are also examined along with their sensitivity.
Chapter 4, “Choosing the Correct Wideband Spectrum Sensing Receiver,” presents the concept of choosing the correct wideband spectrum sensing receiver. The design of the AESA antenna-to-receiver interface is discussed first. The concept of configuring wideband, software-defined DRFM functions is also discussed. Several wideband spectrum sensing architectures are then examined. These include compressive sensing receivers, such as the analog-to-information, Nyquist folding receiver (NYFR), modulated wideband converter, and blind compressive sensing receiver. The impact of the bandpass sampling channelizer is also presented along with polyphase analysis/synthesis channelizers. The author also explains the benefits of the previous subject, which is to reduce the sampling rate and processing. The author then introduces a few commercial devices, such as the integrated transceiver ADRV9009 and the system-on-module software-defined radio that combines the integrated RF agile transceiver Analog Devices AD9361 with the Xilinx Z7035 Zynq-7000 all-programmable system on chip for a scalable multichannel development platform.
Chapter 5, “Transceiver Design and Practical Considerations,” investigates the details of transceiver design, starting with a mathematical model of the transceiver process. This includes the receiver’s process (sampling operations, time uncertainty, clock accuracy, and sampling circuit designs) and the analog-to-digital converter (ADC) transfer function and circuit concepts. For example, a flash converter is used to demonstrate the linearity, quantization error, and noise floor. A mathematical model for the digital-to-analog converter (DAC) is also shown along with an explanation of spurious signal technical issues and limitations. Finally, digitization figures of merit and the direct sampling signal-to-noise ratio (SNR) relationships are derived, and DRFM transceiver design challenges are summarized. There are many very useful equations to calculate the SNR for direct conversion, phase noise, jitter, and figures of merit under various conditions. The author compares several types of ADC/DAC designs and suggests that the flash ADC is a better fit for DRFM design. The author also introduces many practical and typical parameters. This is very useful for everyday design engineers since often parts, subsystems, or systems are too old or too new, and no datasheets can be found. At these times, a “typical value” comes in handy.
Chapter 6, “High-Performance Transceiver Component Technologies,” focuses on transceiver component technologies and architectures. First, it presents the different high-speed comparator designs. Then flash ADC examples in SiGe BiCMOS technology are studied. Time-interleaved techniques are then explored, followed by the pipeline approach and successive approximation. Figure-of-merit plots for the ADC are given for the important technologies. Fin field-effect transistor technologies are also explored. An important requirement of the DRFM transceiver is the embedded, dual-port memory, and several technologies and architectures are shown. Practical considerations are then presented for the output DAC, including ML calibration technology. Direct digital synthesis (DDS) for waveform generation and storage is also discussed, including ROM-based DDS, and the coordinate rotation digital computer is presented. DRFM oscillators and their phase noise and characteristics are also discussed. Chapter 6 also presents the main reasons for timing errors, degradation due to gain variation, and nonuniform sampling effects. It gives many detailed examples of time-interleaved flash, time-interleaved pipeline, and time-interleaved successive approximation register with block diagrams and waveforms.
Chapter 7, “Microwave-Photonic Transceiver Technologies,” begins with a look at the design of microwave photonic transceiver architectures, starting with an overview of the technology used. This includes the mode-locked laser, photodetectors, optical links, and the photonic oscillator. Electro-optical Mach–Zehnder modulators, photonic memories suitable for DRFM transceivers, and microwave photonic antennas are also examined. Photonic ADCs are emphasized; in particular, robust symmetric number system high-resolution encoding with inherent Gray-code properties is presented as a smarter method of folding and quantizing the analog waveforms. The theory and applications of compressive sensing are examined, including the photonic NYFR. Wideband spectrum sensing is presented, and included is a channelizer that uses a fiber Bragg grating. Finally, this chapter looks at wideband S2 crystal technology with its extreme bandwidth capability and its uses in spectrum sensing and DF signal processing. This is a very long chapter; the author dives deep into the subject. The material is challenging to the reader.
In Chapter 8, “Modern Spectral Sensing and Signal Detection Methods,” the author provides an introduction to DRFM signal processing techniques for cognitive and cooperative spectral sensing. These allow the exploitation of underutilized segments of the spectrum, allowing the DRFM transceiver to maneuver highly defended and difficult spectral terrain for exploitation and exploration. Intercepting all of the emitters within the operational arena (both threat and nonthreat) can then lead to good coordination and execution of an EA response, ultimately leading to EMS dominance.
In Chapter 9, “Artificial Intelligence, Machine, and Deep Learning for Spectral Sensing,” AI is presented as an electromagnetic technology method for EMS exploration and exploitation. Understanding the difference between deep learning and ML is emphasized with applications to automatic sensing, detection, and classification of emitters, including unknown emitters that have not previously been encountered. This chapter also walks through how to construct a feature vector from a radar and/or communication signal’s time–frequency and bifrequency detection image. Principal component analysis is used to reduce the size of the feature vector. ML classification algorithms are used to identify, recognize, and specify the particular emitter. A detailed description of a perceptron and a multilayer perceptron classification nonlinear neural network representing the human brain is given.
Chapter 10, “Electronic Attack Using Deep Learning,” discusses EA using deep learning, beginning with spectrum dominance using unmanned aerial vehicles (UAVs). Autonomous UAV navigation using deep reinforcement learning is also presented. Joint EMS operations are discussed along with airborne and surface EAs. Both offensive and defensive EAs are examined. Obscuration EA and deep learning from unmanned combat systems are covered, including the beacon equation, offensive engagement algorithms, cognitive control, and deep reinforcement learning. Selective–reactive EA in smart interference using generative adversarial networks is also covered. Range Doppler imaging signal processing is reviewed, including synthetic aperture signal processing. Deception EA against SAR, including generating noise patches in SAR images, and false targeting EA using deep learning algorithms are presented. The characteristics of target jamming and transponder jamming are examined and compared. Repeater techniques include range gate pull-off, velocity gate pull-off in a coordinated range, and velocity gate pull-off. SAR active decoy EA techniques are discussed as well.
In Chapter 11, “Counter-DRFM Methods,” counter-DRFM techniques are examined and divided into pulse diversity methods and signal processing methods. Pulse diversity techniques involve perturbing the phase of the waveform and orthogonal coding of the waveform on each successive pulse. Signal processing techniques involve several methods, such as polarization discrimination, statistical detection theory using estimation, the Neyman–Pearson receiver, frequency diversity characteristics, and defeating coordinated pull-off using long short-term memory deep learning methods. Countering the coordinated RGVGPO using statistical signal processors and using phase noise measurements is also examined. Finally, the use of converse beam cross-sliding spotlight SAR techniques to avoid DRFM EA is presented.
This book also has online resources that include MATLAB software on the Artech House website. These resources can be used to reproduce many of the results in the book and provide exercises to enhance the learning of the material.
This book is an encyclopedia of digital RF memory and transceiver technologies for electromagnetic warfare. It summarizes thousands of published articles in one book. The author gives detailed explanations, from very basic theorems to very advanced research work. The book is a perfect reference for research scientists and practicing engineers in the electronic warfare environment. Go get one for your bookshelf.
Digital Object Identifier 10.1109/MMM.2023.3256381